不同水分条件下棉花光谱数据对冠层叶片温度的响应特征

利用Fluke热像仪和ASD地物非成像高光谱仪,分别记录棉花新陆早33号、13号2个品种、4个水分处理、5个关键生育时期的冠层红外热图像和反射光谱数据;在红外热图像上提取棉花冠层受光叶片的温度,同时处理高光谱数据获得归一化植被指数(NDVI)、比值植被指数(RVI)、红光620 nm和近红外850 nm波段的反射率(ρ620,ρ850)。分析表明,棉花2个品种4个水分处理的冠层叶片温度(TL)在盛花期、盛花结铃期较高,在盛铃期达到最大值,在开花期和吐絮初期较低;棉花受到水分胁迫,冠层近红外波段光谱的反射率降低,红光波段的反射率升高,NDVI和RVI变小,TL升高;在充分灌溉条件下棉花近红外、红光波段的光谱反射率、NDVI和RVI及TL则与水分胁迫处理的表现相反。和620 nm和850 nm波段反射率与TL的线性相关比较,棉花NDVI和RVI与TL的线性相关性更强。研究表明,将红外热图像和高光谱遥感技术相结合,具有实时、非破坏性地监测棉花水分状况的潜力。

The Responsive Characteristics between Cotton Canopy Leaves Temperature from Infrared Thermography and Hyperspectral Data under Different Water Conditions

Hyperspectral reflectance data were recorded by the ASD portable non-imaging hyperspectral spectrometer at five growth stages of cotton in an experimental field including two cotton cultivars, Xinluzao No.33, No.13, with four water treatments and cotton canopy thermal images were taken with a Fluke radiometric infrared video camera, thermal images can be used to extract canopy sunlit leaves temperature(T_L). Meanwhile, hyperspectral data were processed to calculate the normalized difference vegetation index(NDVI), ratio vegetative index（RVI）, reflectance at red spectrum 620 nm and near-infrared 850 nm wavelength(ρ₆₂₀, ρ₈₅₀), respectively. The results showed that canopy leaves temperature(T_L) of two cotton cultivars with four water treatments reached the higher value at full flowering stage, full flowering and boll-forming stage, their maximum value were both at full boll stage, the lower T_L both occurred at flowering stage and initial open boll stage. Cotton reflectance were reduced at near-infrared and increased at red spectrum wavelength, corresponding NDVI and RVI were less, T_L was greater in water stressed plots. The spectrum reflectance at red and NIR wavelength, NDVI, RVI and T_L were opposite variation at full water plots than these parameters at water stress treatments. The relationships between NDVI, RVI and T_L（rNDVI-TL= -0.4518^**，rRVI-T_L= -0.5274^**，n=38, α=1%）were both stronger than the relationships between ρ₆₂₀, ρ₈₅₀ and T_L, respectively. It showed that combination of infrared thermography and hyperspectral remote sensing technology have potential to rapidly and nondestructively monitor water status of cotton.